Researcher, Robot Learning

About Menlo Menlo Research is an Applied R&D lab building Asimov, an open-source humanoid robot platform, and the full software stack that powers it. Our mission is to make humanoid labor economically viable, turning software into physical labor at scale. We build across the full stack: hardware architecture, locomotion, autonomy, simulation, and infrastructure. We move fast, ship to real robots, and open-source everything we can. If you want your work to matter beyond a paper or a demo, this is the place. The Role Asimov’s promise is a humanoid that learns: one that discovers new skills and gets better the more it works. You’ll build the learning systems that make that true. As a Researcher in Robot Learning on our Brain team, you’ll own the methods that turn data into general-purpose behavior on Asimov. Our locomotion and manipulation researchers push specific skills; you’ll work on the layer underneath and across them. That means generalist policies, the data that trains them, and the loops that let Asimov improve from its own experience. You’ll train on real robot data, ship to real hardware, and open-source what you can. What You’ll Do Own Asimov’s generalist policy research end to end, taking each idea from a hypothesis and a dataset to a trained policy running on the physical robot Train and post-train vision-language-action models and other generalist policies that follow instructions and transfer across tasks and environments Build imitation learning pipelines on